Regression testing is considered as a separate forms of testing attached with performance testing where tester runs old test suits after each change made to system. It will be a big problem in testing the service-oriented software (SOS), where each system component is inherently agile and changes its behavior dynamically. These agile component gives a big rise to big problem in the regression testing process with respect to complexity, time complexity and cost complexity. A service-oriented software may change in case of bug fixing, adaptation of new environment, upgrading or updating functionality in order to improve performance or it is demanded by customer. After the software is delivered to customer the service oriented software must be regressed to validate that there is no defects. We present a hierarchical regression test selection algorithm for service-oriented software, and evaluate it in service-oriented environment along with results.
Over the year’s thunderstorms have been one of the major causes of death and one of the most catastrophic natural calamities in the country and the most challenging part is the prediction of thunderstorm beforehand, because of the random nature of our atmosphere. Through this research paper the attempt was made to do analyze the atmospheric stability indices (atmospheric instability causes thunderstorms) using INSAT-3D sounder data to predict thunderstorms by predicting their values using machine learning approach. By setting the indices possess a threshold value and also there is predictability in the data which can be used to predict their future values. The tephigram is used by meteorologist, scientist, weather observer, pilots to solve atmospheric temperature and humidity problems using simple graphical techniques. We can avoid extensive calculation for the mathematical relationships to generate diagram to predict the events. Meteorologists use the thermodynamic diagram daily to forecast cloud height and atmospheric stability and using the tephigram is use to generate and integrate LIVE events to show easier for the users to view the thermodynamic diagram instantly.
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